In-line Inspection(ILI) 기반 확률론적 구조적 파손 예측

Abstract

Underground water supply pipelines are prone to functional deterioration and damage because of the occurrence and growth of corrosion over time. Therefore, to ensure the safety of such pipelines, their service life should be accurately predicted using precise inspection information. For this purpose, in-line inspection is applied for diagnosing pipelines. In this study, the structural safety of a water supply pipeline in Korea was evaluated by applying Monte-Carlo simulation, which is a stochastic analysis method, to the corrosion information of large-diameter water pipes obtained through a magnetic flux leakage sensor. For this purpose, the most appropriate probability distribution function and parameters were estimated through the statistical analysis of the data obtained from the sensor, and the corrosion growth was estimated using the probability distribution function determined from the simulation results. The safety factors for the internal pressure and external load for each pipe, which depended on the corrosion growth, could be derived probabilistically. Thus, the structural safety deterioration of the pipe over time could be estimated, and an appropriate rehabilitation method was proposed. In addition, the optimum rehabilitation time could be determined. This study will provide guidelines for the rehabilitation of water supply pipelines.